python
170 Seats
Basic Information
Apply Now

Course Description

Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis

What are the Python Course Pre-requisites

There are no hard pre-requisites. Basic understanding of Computer Programming terminologies is sufficient. Also, basic concepts related to Programming and Database is beeficial but not mandatory.

Objectives of the Course

  • To understand the concepts and constructs of Python
  • To create own Python programs, know the machine learning algorithms in Python and work on a real-time project running on Python

Who should do the course

  • Big Data Professionals
  • IT Developers
  • Those who are showing interest to build their career in Python

Course Syllabus

  • Introduction to Languages
  • Introduction to Python
  • Python Language Fundamentals
  • Different Modes of Python
  • Python Variables
  • Input & Output Operators
  • Control Statements
  • List Collection
  • Tuple Collection
  • Set Collection
  • Dictionary Collection
Functions
  • Packages
  • OOPs
  • Overriding
  • Overloading
  • Exception Handling & Types of Errors
  • Regular expressions
  • File & Directory handling
  • Python Logging
  • Date & Time module
  • Multi-threading & Multi Processing
  • Garbage collection
  • Python Data Base Communications(PDBC)
  • Python – Network Programming
  • Tkinter & Turtle
  • Data analytics modules
  • DJANGO
  • Pandas – Introduction to Data Structures
  • Pandas — Series
  • Pandas – DataFrame
  • Pandas – Panel
  • Pandas – Basic Functionality
  • Pandas – Descriptive Statistics
  • Pandas – Function Application
  • Pandas – Reindexing
  • Pandas – Iteration
  • Pandas – Sorting
  • Pandas – Working with Text Data
  • Pandas – Options and Customization
  • Pandas – Indexing and Selecting Data
  • Pandas – Statistical Functions
  • Pandas – Window Functions
  • Pandas – Aggregations
  • Pandas – Missing Data
  • Pandas – GroupBy
  • Pandas – Merging/Joining
  • Pandas – Concatenation
  • Pandas – Categorical Data
  • Pandas – Visualization
  • Pandas – IO Tools
  • NUMPY − DATA TYPES
  • NUMPY − ARRAY ATTRIBUTES
  • NUMPY − ARRAY CREATION ROUTINES
  • NUMPY − ARRAY FROM EXISTING DATA
  • NUMPY − ARRAY FROM NUMERICAL RANGES
  • NUMPY − INDEXING & SLICING
  • NUMPY − ADVANCED INDEXING
  • NUMPY − ITERATING OVER ARRAY
  • NUMPY – ARRAY MANIPULATION
  • NUMPY – BINARY OPERATORS
  • NUMPY − ARITHMETIC OPERATIONS
  • NUMPY − STATISTICAL FUNCTIONS
  • NUMPY − SORT, SEARCH & COUNTING FUNCTIONS
  • NUMPY − BYTE SWAPPING
  • NUMPY − COPIES & VIEWS
  • NUMPY − MATRIX LIBRARY
  • NUMPY − LINEAR ALGEBRA
  • NUMPY − MATPLOTLIB
  • NUMPY – HISTOGRAM USING MATPLOTLIB
  • NUMPY − I/O WITH NUMPY